Welcome to the repository for the Machine Learning-Based Systems Projects course (DCA0305) at the Federal University of Rio Grande do Norte! Here, I showcase the projects I developed during this course, ranging from fundamental coding practices to comprehensive MLOps projects involving cutting-edge Natural Language Processing (NLP) algorithms.
MLOps is an innovative approach that harmonizes the development, training, and deployment of machine learning (ML) models into a continuous and automated process. It integrates DevOps principles and tools with the unique challenges of the ML lifecycle, incorporating web development practices. This synergy streamlines the entire ML journey, ensuring efficiency and reliability. Check out the visualization below to get a glimpse of this seamless integration:
Explore the projects below and witness the evolution of MLOps through my work:
Dive into the world of best programming practices through three distinct projects from the Dataquest.io platform. This module emphasizes code refactoring techniques, clean code principles, and advanced exception handling. Enhance your coding skills by exploring this project.
This repository was created by Mariana Brito Azevedo, enrolled in the Machine Learning-Based Systems Projects course (DCA0305) at the Federal University of Rio Grande do Norte.
This repository is under MIT License, you can check it here